docs: def get_ddG_results(self):
          """Parse the results from BuildModel and get the delta delta G's.
  
          A positive ddG means that the mutation(s) is destabilzing, negative means stabilizing.
  
              - highly stabilising (ΔΔG < −1.84 kcal/mol);
              - stabilising (−1.84 kcal/mol ≤ ΔΔG < −0.92 kcal/mol);
              - slightly stabilising (−0.92 kcal/mol ≤ ΔΔG < −0.46 kcal/mol);
              - neutral (−0.46 kcal/mol < ΔΔG ≤ +0.46 kcal/mol);
              - slightly destabilising (+0.46 kcal/mol < ΔΔG ≤ +0.92 kcal/mol);
              - destabilising (+0.92 kcal/mol < ΔΔG ≤ +1.84 kcal/mol);
              - highly destabilising (ΔΔG > +1.84 kcal/mol).
  
          Returns:
              dict: Dictionary of mutation group to predicted ddG.
  
          """
          foldx_avg_df = self.df_mutation_ddG_avg
  
          foldx_avg_ddG = {}
          results = foldx_avg_df[['Pdb', 'total energy', 'SD']].T.to_dict().values()
          for r in results:
              ident = r['Pdb'].split('_')[-1]
              ddG = r['total energy']
              ddG_sd = r['SD']
  
              foldx_avg_ddG[self.mutation_index_to_group[int(ident)]] = (ddG, ddG_sd)
  
          return foldx_avg_ddG